Research On Electric Vehicle Logistics Distribution Routing Problem Considering Charging Demand

With the increasingly serious problems of energy shortage and environmental pollution,electric vehicles have been vigorously promoted in recent years.Considering the high energy consumption and high pollution,affected by policy promotion and other factors,it began to use electric vehicles more and more to carry out the task of urban logistics branch distribution in the logistics industry.However,at this stage,the electric logistics vehicles are limited by the mileage,and they often need to be charged in the distribution process.In addition,due to the insufficient coverage of the charging station and the driver’s mileage anxiety,the selection of distribution route has become a difficult problem.What’s more,the current logistics enterprises also lack of unified planning for the distribution task of electric vehicles.The operation characteristics of electric logistics vehicle determine that it is quite different from traditional routs planning of general fuel vehicles,especially the selection of charging station greatly increases the complexity of the problem.Therefore,it’s crucial to propose an effective electric vehicle routs planning model with its algorithm and build an application system platform for relevant enterprises.The following is the main research content of this paper:（1）This paper reviews the research progress of Electric Vehicle Routing Problem（EVRP）,a new branch of Vehicle Routing Problem（VRP）in recent ten years,and obtains the theoretical basis of the problem.Truck drivers at logistics outlets were investigated and interviewed to get the current situation of actual production in the industry.Combined with theory and practice,this paper puts forward the problem model CEVRPTW（Capacitated Electric Vehicle Routing Problem with Time Windows）with capacity constraint and unilateral soft time window and considering charging endurance,and gives the assumption premise,symbolic expression,constraint conditions and solution formula of the model.（2）CEVRPTW is a typical EVRP problem.Therefore,this paper firstly summarizes the EVRP researches considering the charging problem,and then summarizes the two most commonly used chromosome coding methods（i.e.mapping rules）when using Genetic Algorithm to solve the problem: Charging Station Direct Coding Algorithm（DC Algorithm）and Charging Station Nearest Neighbor Insertion Algorithm（NNI Algorithm）.Based on advantages and disadvantages of these two algorithms,Comprehensive Analysis Insertion Algorithm（CAI Algorithm）is proposed:The charging station does not directly participate in chromosome coding,but there are three schemes,including front nearest neighbor,back nearest neighbor and the best sum on each alternative arc segment,are all considered when decoding.and then it selects the optimal position to insert.Then,this paper gives the mathematical proof that CAI Algorithm is better than the other two.Using Python and based on computing framework Geatpy,the three algorithms are implemented,and several groups of simulation examples are designed to test them.The results show that the feasible solution rate and upper limit of optimization of CAI Algorithm are the best.The average solution results in all tests are better than other algorithms.The objective function value can be saved by 5%-20%.However,the executing efficiency of CAI is also the lowest of the three.The executing time is more than twice that of other algorithms.（3）Taking the managers of logistics enterprises as the user object,a set of logistics distribution routs planning system is developed in this paper.The system is based on B/S architecture and WebGIS technology.The system takes CAI as the algorithm module,adding a circult cache strategy proposed in this paper.The executing time can be saved by about 95% using the strategy in the experimental test,which perfactly solves the problem of low executing efficiency of CAI Algorithm.The functions of routing and displaying are realized through Baidu Map API SDK,which makes the routing results accurate and the map interactive friendly.The front-end system is based on Vue.js and the back-end system is based on Spring Boot,which realizes the complete separation of the front-end and back-end.It reduces the coupling of the whole system,enhancing the maintainability and scalability.Users can managing vertexes,vehicles and other data over both map and backstage on their browsers,which is clear to view and easy to operate.The problem model CEVRPTW and the algorithm CAI proposed in this paper enrich the relevant theories in the field of EVRP.The developed logistics distribution routs planning system provides technical support for logistics enterprises to reduce the operation costs.